The Complicated Inadequacy of Race and Ethnicity Data

Abstract

The Complicated Inadequacy of Race and Ethnicity Data "Choose from the options below." This seemingly innocuous prompt embedded in countless daily medical registrations aims to capture race and ethnicity. Yet, as mothers of children with multiple racial and ethnic identities, a prompt that could take just moments sometimes becomes a weighted pause, reminding us of the intersectional reality of our families. How do we represent the Thai and non-Hispanic White; Cuban and Vietnamese; Colombian, non-Hispanic Black, and non-Hispanic White backgrounds, roots, and cultures that our children embody? Which box or boxes do we check off?Selecting every possibly relevant box might imply that our children are counted as their whole selves, described by each part within. But do we also try to anticipate their eventual self-determined identity that will coalesce with their socially assigned one, as both may contribute to their health status? 1 Or, we can reflex to "other," recognizing that any collection of small boxes will never equal the sum of their inherited legacies or gathered experiences, a critical acknowledgment as we seek to disentangle the drivers of disparate health outcomes. But, if we designate our children as "other," how will they be accurately ascribed risk in clinical practice or research?The weight of the pause and the many different approaches to these questions are not just informed by our own lived experiences and what we understand about the world. They are questions we ponder deeply because, in addition to mothers, we are physicianscientists. We know that our children-with their specific family ancestries-are unlikely to be meaningfully represented in our own result tables. By selecting "other," we relegate them to exclusion from many data analyses, decreasing not only their contribution to the advancement of health care systems research but also any benefit children like them might receive because we have obscured them into a box that is uninterpretable. By selecting their specific combinations of races and ethnicities among the options available, they are equally uninterpretable within the typically resultant multiracial category given the infinite combinations contained within.These are not outlier considerations for just our own children. The 2020 US Census has shown that when given the opportunity, there are many of us who view our family heritage in complex ways that do not fit neatly within a handful of boxes. As of 2020, "some other race" was the second most common racial category selected, an option chosen for 49.9 million people. 2 The multiracial population in the US increased by 276%, from 9 million in 2010 to 33.8 million in 2020. These large shifts likely represent a combination of real population change along with the improved methodologies to select options that reflect self-perceptions. But it also means

Insights into turning points from the perspective of young people with out-of-home care experience: events, impact and facilitators of change

“…Slightly over half (54.0%) of the participants identified as Latinx/Hispanic, 48.8% as White, 28.8% as American Indian, and 27.4% as Black/African American. Race and ethnicity were coded in non-exclusive categories, as in the US (and especially among families involved in the child welfare system), there are high rates of racial/ethnic overlap and it is problematic to place children who self-identify as multi-racial or multi-ethnic into a single category (Chaiyachati et al, 2022). Participants’ mean age in young adulthood was 19.5 years ( SD = .94).…”

Scoring Quality, Scoring Equity: The Promise and Power of Scorecards to Facilitate Bidirectional, Real-Time Communication

“…Such efforts are revealing of data practices overall and may clarify resource allocation needs, both within existing data infrastructure and in community-specific outcomes. 14 Quality scorecards may also elucidate patterns of practice variation in smaller centers that may differ from those reported in larger centers or captured in pooled data. For example, much of the data obtained by collaboratives like the Vermont-Oxford Network are infrequently available for interpretation and application in real time and are reported in the aggregate, thus potentially obscuring subpopulation trends.…”

Breaking Down the Boxes—Time to Reshape Demographic Data

“…To the Editor We read with great interest the article highlighting the nuanced, complex, and inadequate check-box system of identifying race and ethnicity. The authors astutely argue that current demographic collection methods are flawed and fail to recognize multiracial and multiethnic individuals, thereby compromising clinical care and research.…”

“…Our research team includes a South Asian American advocate for patients with Crohn disease who experiences “the weight of the pause” described by the authors when pondering which demographic box to check. Asian/Pacific Islander, White, and other do not appropriately or accurately describe her background or self-identity.…”

“…In addition to action items identified in the article, we propose the creation of a consensus panel to reshape demographic reporting methods. For example, Asia can be more accurately classified as Far East Asia, Middle East/North Africa, South Asia, and Southeast Asia, and the term Black can be replaced with identities such as African, African American, Caribbean, Latin American, and South American.…”